Feature Shift Detection: Localizing Which Features Have Shifted via
Conditional Distribution Tests

Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests

14 July 2021

David I. Inouye

ArXiv (abs)PDF HTML

Papers citing "Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests"

9 / 9 papers shown

Title
Feature Shift Localization Network Míriam Barrabés D. M. Montserrat Kapal Dev A. Ioannidis OOD 47 0 0 10 Jun 2025
"Who experiences large model decay and why?" A Hierarchical Framework for Diagnosing Heterogeneous Performance Drift Harvineet Singh Fan Xia Alexej Gossmann Andrew Chuang Julian C. Hong Jean Feng 28 0 0 31 May 2025
Explaining Concept Shift with Interpretable Feature Attribution Ruiqi Lyu Alistair Turcan Bryan Wilder FAtt 51 0 0 27 May 2025
Interpretable Model Drift Detection Pranoy Panda Kancheti Sai Srinivas V. Balasubramanian Gaurav Sinha 212 1 0 09 Mar 2025
Learning Run-time Safety Monitors for Machine Learning Components Ozan Vardal Richard Hawkins Colin Paterson Chiara Picardi Daniel Omeiza Lars Kunze Ibrahim Habli 70 0 0 23 Jun 2024
Online Distribution Shift Detection via Recency Prediction Rachel Luo Rohan Sinha Yixiao Sun Ali Hindy Shengjia Zhao Silvio Savarese Edward Schmerling Marco Pavone 91 10 0 17 Nov 2022
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts Haoran Zhang Harvineet Singh Marzyeh Ghassemi Shalmali Joshi 70 23 0 19 Oct 2022
Towards Explaining Distribution Shifts Sean Kulinski David I. Inouye OffRL FAtt 108 28 0 19 Oct 2022
MLDemon: Deployment Monitoring for Machine Learning Systems Antonio A. Ginart Martin Jinye Zhang James Zou 135 20 0 28 Apr 2021